fixing rbin

AnestisTouloumis · Jul 25, 2019 · 1c26593 · 1c26593
1 parent 4c627e9
commit 1c26593
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Showing 2 changed files with 24 additions and 48 deletions.
diff --git a/R/rbin.R b/R/rbin.R
@@ -102,40 +102,28 @@
 #' beta_coefficients <- 0.2
 #' latent_correlation_matrix <- toeplitz(c(1, 0.9, 0.9, 0.9))
 #' x <- rep(rnorm(sample_size), each = cluster_size)
-#' simulated_binary_dataset <- rbin(
-#'   clsize = cluster_size,
+#' simulated_binary_dataset <- rbin(clsize = cluster_size,
 #'   intercepts = beta_intercepts, betas = beta_coefficients,
-#'   xformula = ~x, cor.matrix = latent_correlation_matrix, link = "probit"
-#' )
+#'   xformula = ~x, cor.matrix = latent_correlation_matrix, link = "probit")
 #' library(gee)
-#' binary_gee_model <- gee(y ~ x,
-#'   family = binomial("probit"), id = id,
-#'   data = simulated_binary_dataset$simdata
-#' )
+#' binary_gee_model <- gee(y ~ x, family = binomial("probit"), id = id,
+#'   data = simulated_binary_dataset$simdata)
 #' summary(binary_gee_model)$coefficients
 #'
 #' ## See Example 3.6 in the Vignette.
 #' set.seed(8)
 #' library(evd)
-#' simulated_latent_variables1 <- rmvevd(sample_size,
-#'   dep = sqrt(1 - 0.9),
-#'   model = "log", d = cluster_size
-#' )
-#' simulated_latent_variables2 <- rmvevd(sample_size,
-#'   dep = sqrt(1 - 0.9),
-#'   model = "log", d = cluster_size
-#' )
+#' simulated_latent_variables1 <- rmvevd(sample_size, dep = sqrt(1 - 0.9),
+#'   model = "log", d = cluster_size)
+#'   simulated_latent_variables2 <- rmvevd(sample_size, dep = sqrt(1 - 0.9),
+#'   model = "log", d = cluster_size)
 #' simulated_latent_variables <- simulated_latent_variables1 -
 #'   simulated_latent_variables2
-#' simulated_binary_dataset <- rbin(
-#'   clsize = cluster_size,
+#' simulated_binary_dataset <- rbin(clsize = cluster_size,
 #'   intercepts = beta_intercepts, betas = beta_coefficients,
-#'   xformula = ~x, rlatent = simulated_latent_variables
-#' )
-#' binary_gee_model <- gee(y ~ x,
-#'   family = binomial("logit"), id = id,
-#'   data = simulated_binary_dataset$simdata
-#' )
+#'   xformula = ~x, rlatent = simulated_latent_variables)
+#' binary_gee_model <- gee(y ~ x, family = binomial("logit"), id = id,
+#'   data = simulated_binary_dataset$simdata)
 #' summary(binary_gee_model)$coefficients
 #' @export
 rbin <- function(clsize = clsize, intercepts = intercepts, betas = betas,

diff --git a/man/rbin.Rd b/man/rbin.Rd